標題: Integrating expert profile, reputation and link analysis for expert finding in question-answering websites
作者: Liu, Duen-Ren
Chen, Yu-Hsuan
Kao, Wei-Chen
Wang, Hsiu-Wen
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: Community;Expert finding;Question answering;Link analysis;User reputation;Yahoo! Answer Taiwan
公開日期: 1-一月-2013
摘要: Question answering websites are becoming an ever more popular knowledge sharing platform. On such websites, people may ask any type of question and then wait for someone else to answer the question. However, in this manner, askers may not obtain correct answers from appropriate experts. Recently, various approaches have been proposed to automatically find experts in question answering websites. In this paper, we propose a novel hybrid approach to effectively find experts for the category of the target question in question answering websites. Our approach considers user subject relevance, user reputation and authority of a category in finding experts. A user's subject relevance denotes the relevance of a user's domain knowledge to the target question. A user's reputation is derived from the user's historical question-answering records, while user authority is derived from link analysis. Moreover, our proposed approach has been extended to develop a question dependent approach that considers the relevance of historical questions to the target question in deriving user domain knowledge, reputation and authority. We used a dataset obtained from Yahoo! Answer Taiwan to evaluate our approach. Our experiment results show that our proposed methods outperform other conventional methods. (C) 2012 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.ipm.2012.07.002
http://hdl.handle.net/11536/21085
ISSN: 0306-4573
DOI: 10.1016/j.ipm.2012.07.002
期刊: INFORMATION PROCESSING & MANAGEMENT
Volume: 49
Issue: 1
起始頁: 312
結束頁: 329
顯示於類別:期刊論文


文件中的檔案:

  1. 000313466600022.pdf